『Supply ChAInge』のカバーアート

Supply ChAInge

Supply ChAInge

著者： Derek Aranda
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Join supply chain expert Derek Aranda for a series investigating the challenges and opportunities of cognitive supply chains. We interview enterprise-level experts in AI, risk, change management, ethics, HR, and logistics to gain an understanding of the real-life implementation and impact behind intelligent supply chain management. Like all good investigations, our conclusion is not a foregone one, as complex systems require complex analysis, and the cutting edge of technology, well, it can be sharp.Join us on Supply ChAInge to ask the question behind the question: not just can a cognitive supply chain work, but what does it take at scale? 経済学
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  • Visibility Is Table Stakes: Grant Ritchie on Trust, Data, and the Next Frontier of Logistics

    Visibility Is Table Stakes: Grant Ritchie on Trust, Data, and the Next Frontier of Logistics
    2026/10/08
    Grant Ritchie of Freedom Trans USA joins Supply ChAInge to trace how "visibility" evolved from a pin on a delivery map into a full decision-support system spanning condition, upstream materials, and predictive resilience. Derek and Grant cover the "Amazon effect" that reset customer expectations, why most mid-size shippers are still far from a 20-screen command center, and why AI is more likely to absorb repetitive tasks like rate confirmations than to replace trust-based freight relationships. They close on the blockchain hype cycle as a cautionary tale, and why "we've always done it this way" is often justified inertia, not simple resistance. 🎧 Episode Highlights [2:07] Grant's career path from oil and gas trucking in South Texas and North Dakota to Freedom Trans USA. [6:37] What visibility means today across asset, asset-light, and platform-based logistics, and how the Amazon effect raised the bar for every mode of freight, not just parcel. [11:05] Why most companies, especially mid-size shippers, are still far from the "20-screen command center" fantasy, and how Grant helps customers figure out what they actually need instead of selling every tool available. [18:48] The AI-as-replacement fear, and why the blockchain hype cycle is Grant's go-to cautionary tale for evaluating today's AI claims. [22:32] The real AI tools that are already showing up in freight, including a bot built to sit on top of existing TMS platforms and handle repetitive tasks like rate confirmations and carrier vetting. [30:11] Visibility as decision quality — using real-time data to reroute around disruptions like a closed Strait of Hormuz, including shifting port strategy toward Mexico. [35:19] "Shipper of choice" and the cost of change — why an hour-and-a-half load time versus a 15-minute one is a wake-up call most companies need data, not opinion, to see. 🔑 Key Takeaways Visibility now spans condition, upstream material availability, and predictive resilience — the goal is better and faster decisions, not just faster information. AI is more likely to absorb repetitive tasks (rate confirmations, carrier vetting, tendering) than replace freight relationships. Blockchain's hype cycle is a useful reminder that "this changes everything" often overstates the change. Adoption is a trust and change-management problem before a technology one. "We've always done it this way" is often justified inertia — what moves people is showing true logistics cost, not a generic pitch. 🧭 Frameworks Worth Saving The visibility maturity ladder: (1) where is my shipment — the baseline; (2) what condition is it in — temp, humidity, quality; (3) what's happening across my network — tier 1–3 supplier visibility; (4) predictive and prescriptive — building contingency plans before disruption hits. Justified inertia: "We've always done it this way" is often a legitimate response from a company that's been successful. What moves the conversation is a true-cost picture and a concrete comparable example, not a generic pitch. The blockchain test: before assuming a technology will replace a function, ask whether the hype resembles blockchain's. The tool usually has real value, but total-replacement predictions tend to be overstated. 💬 Notable Quotes Visibility these days is really table stakes. If you don't have visibility, you can't operate. Grant Ritchie Logistics is a true collaboration from everybody involved, and all it takes is one bad apple to gum up the works. Grant Ritchie 👤 About The Guest Grant Ritchie, Freedom Trans USA Grant Ritchie has spent his career viewing logistics and visibility from nearly every angle in the industry. He started in oil and gas trucking across South Texas and North Dakota's major shale plays, then moved to the customer side importing oil country tubular goods, where his company became the largest importer of break bulk pipe into the Port of Houston. From there, he moved into operations and procurement at Ryder Integrated Logistics, then sales at XPO Logistics, and now works at Freedom Trans USA, which combines its own asset fleet with brokerage and managed transportation services across the lower 48, Mexico, and parts of Canada. 🎙️ About The Host Derek Aranda Derek Aranda spent over two decades as a global executive operating across commercial, supply chain, and digital transformation roles at scale. That span across the full value chain shapes his lens: the decisions, incentives, trust, economics, and governance that determine whether technology actually works inside real supply chains. On Supply ChAInge, he pressure-tests the autonomous future and helps leaders shape the framework to build it on their own terms. Stay Connected: supplychaingepodcast.com Produced by Speakerbox Media
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    40 分
  • Supply Chain Transformation: AI Can't Enforce Culture (with Sanchay Roy)

    Supply Chain Transformation: AI Can't Enforce Culture (with Sanchay Roy)
    2026/09/25
    Sanchay Roy on supply chain transformation: AI can't enforce culture, but it can capture frontline operator knowledge before the retirement clock runs out. Drawing on 34 years leading continuous improvement and manufacturing excellence at GE, Philips, and Shell, Sanchay joins Derek in the make pillar of the supply chain to unpack Lean's hardest lesson and why it applies directly to AI: culture, not tools, decides whether change sticks. They dig into the tacit knowledge MES and SCADA systems never record, why operators judge a new tool within weeks, and how turning AI-driven transparency into blame instead of learning can undo earned trust far faster than it was built. 🎧 Episode Highlights [5:41] Continuous improvement in the analog world: Gemba, shifts spent watching a process, and how leadership habit becomes culture. [8:36] The hardest lesson from Lean: one change agent doesn't change the culture. When the talent leaves, performance slides back. [11:23] The retirement clock: a large share of the Western manufacturing workforce is nearing retirement, and its knowledge will walk out the door. [16:08] "You are asking us to become robots": a Dutch plant manager's pushback on Lean, and how standard work freed creativity for real problems. [17:17] AI can't enforce culture, but it can keep continuous improvement from becoming episodic. [23:08] You can't buy operator knowledge off the shelf, and how AI can turn unstructured observations into shared enterprise knowledge. [29:20] Transparency cuts both ways: learn from the root causes AI surfaces, or turn them into KPI chasing and blame. [34:46] AI is not gospel truth: repeating Lean's commandments mistake versus embracing AI through rapid PDCA cycles. [36:00] Trust comes walking, but leaves galloping on a horse. [37:42] Closing thought: operators give a new tool two to three weeks, and they will price the change more accurately than finance. 🔑 Key Takeaways AI will not change your culture; leadership practice does. Leaders who expect AI to drive cultural change will repeat Lean's mistake, only faster, because AI amplifies whatever culture it lands in. Your systems know what happened; your operators know why. MES and SCADA capture data after the event. The operator knows the humidity is curling labels, the rubber flecks mean a belt is wearing, the motor's pitch means it needs lubrication. That knowledge can't be bought off the shelf. Transparency is a choice leaders make, not a feature AI provides. Once AI surfaces the root causes behind line performance, leaders can use that truth to learn or to assign blame. Turn it into KPI chasing and operators stop engaging. 💬 Notable Quotes Cultural change is probably the most challenging aspect of any transformation. Sanchay Roy AI cannot enforce culture. Nothing can. But what AI can do is prevent CI from becoming episodic. Sanchay Roy They always tell you what has happened. The operator knows why it has happened. Sanchay Roy The trust comes walking, but leaves galloping on a horse. Sanchay Roy 👤 About The Guest Sanchay Roy, Operational Excellence and Transformation Leader Sanchay Roy spent 34 years leading business improvement and operational excellence across energy, oil and gas, lighting, consumer goods, and process and discrete manufacturing. A GE Certified Master Black Belt, he spent 14 years at GE before leading business excellence for Philips' lighting business across 61 assets. At Shell, he drove continuous improvement for capital projects, improved the upstream oil and gas supply chain, and led manufacturing excellence for the Lubricants business across 32 sites. Transformations he led have been recognized as Best Run Supply Chain and with an EU Manufacturing Excellence award. He is co-author, with Stewart Dunbar, of Improving Supply Chains in the Oil and Gas Industry (Springer). Sanchay now works with startups, bringing Lean, Design Thinking, and fact-based problem solving to new ventures. 🎙️ About The Host Derek Aranda Derek Aranda spent over two decades as a global executive operating across commercial, supply chain, and digital transformation roles at scale. That span across the full value chain shapes his lens: the decisions, incentives, trust, economics, and governance that determine whether technology actually works inside real supply chains. On Supply ChAInge, he pressure-tests the autonomous future and helps leaders shape the framework to build it on their own terms. Stay Connected: supplychaingepodcast.com april12advisors.com Produced by Speakerbox Media
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    40 分
  • Implementing AI in Supply Chain: Stop Bolting AI Onto the Old Process (with Narahari Rao)

    Implementing AI in Supply Chain: Stop Bolting AI Onto the Old Process (with Narahari Rao)
    2026/09/10
    Narahari Rao of SLB on implementing AI in supply chain: why bolting AI onto old processes is like plugging a motor into horse-and-carriage infrastructure, and why a successful supply chain should be invisible to the customer. The conversation covers the engineering mindset that makes for stronger procurement negotiators, why digitization doesn't require 100% clean data to get started, the case for narrow, edge-of-the-ERP use cases over full-process overhauls, and how to embed risk management directly into the workflow instead of leaving it stranded in a dashboard nobody opens. 🎧 Episode Highlights [4:03] How an engineering mindset makes for strong procurement negotiators. You don't need the deep technical expertise, but you need to know enough. [8:46] The digitization starting point. Harmonizing data across ERPs doesn't require 100% clean data. Roughly 70% good data is enough to begin. [12:40] Thinking backward from the customer instead of function by function, and why procurement too often feels disconnected from who it ultimately serves. [17:56] The Model T analogy. Why bolting AI onto an existing process just builds a better horse-drawn carriage instead of designing the automobile. [23:06] Dashboards are where insights go to die. Why risk data still needs a human to interpret it, and where AI can actually help. [29:33] Embedding risk management directly into the sourcing workflow, instead of asking buyers to jump between disconnected systems to connect the dots. [34:14] The supplier outage story. A single hidden raw-material dependency shut down a "backup" supplier too, and what that reveals about the illusion of multi-sourcing. [39:34] Building narrow, purpose-built AI agents for known risks. Hurricanes today, wildfires or cyber threats tomorrow. [52:28] Lean roots at Toyota and why continuous improvement is a cultural shift, not a one-time initiative. [55:22] The case for starting with front-line pain points. Small, fast wins build the ROI story before you attempt large-scale transformation. 🔑 Key Takeaways · A successful supply chain is invisible to the customer. The product shows up at the right time, cost, and quality without the customer ever having to think about how it got there. That outcome, not process optimization for its own sake, should anchor every transformation decision. · You don't need perfect data to start. Waiting for 100% clean, harmonized data before beginning a digitization journey is a common trap. Roughly 70% good data is enough to start building insight and momentum. · Multi-sourcing isn't real risk mitigation if your suppliers share a hidden dependency. A "backup" supplier that draws from the same raw-material source, region, or single point of failure as your primary supplier isn't actually diversification. The risk is just one layer removed. 🧭 Frameworks Worth Saving · Work backward from the customer, not forward from your function. Hari's approach to scoping any transformation: define who the customer actually is (internal or external), then work backward from what they need to experience through planning, sourcing, and logistics. The goal is resisting the pull to optimize each function in its own silo, disconnected from that end goal. · Look at the edges of the ERP before rebuilding the core. Where Hari sees AI use cases pay off first: start with a narrow, well-defined question, like "when will this product show up at my desk?", and use existing ERP data, stepping slightly outside the walled garden to answer it, rather than optimizing the whole sourcing process before proving value at the edges. · Embed risk management inside the workflow, not next to it. The pattern for making risk management usable at scale: build risk checks into the intake process itself rather than a separate tool buyers have to remember to check, avoid siloed systems that require manually connecting the dots across screens, and build a bespoke model matched to your company's policies and culture rather than tying yourself to a vendor's release schedule. 💬 Notable Quotes A successful supply chain is one which makes the consumer not think about how that product actually showed up at their door. Narahari Rao You don't actually have to have 100% clean data before you actually progress on this journey. Narahari Rao Lean is not something you do just at your workplace. It's a cultural shift. Narahari Rao 👤 About The Guest Narahari Rao, Global Procurement Risk and Resilience Director, SLB Narahari Rao is the Global Procurement Risk and Resilience Director at SLB, where he manages supply base risk across 30 global business units. With over 20 years of experience in supply chain, strategic sourcing, and engineering, he specializes in building resilient supply networks for complex global operations. He holds a Master of Science in Mechanical Engineering from Texas A&M University and is a Certified Lean Six Sigma Champion. Throughout his career, Narahari has ...
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    59 分
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